Properties and applications of the Kirkwood–Dirac distribution

Abstract There are several mathematical formulations of quantum mechanics. The Schrödinger picture expresses quantum states in terms of wavefunctions over, e.g. position or momentum. Alternatively, phase-space formulations represent states with quasi-probability distributions over, e.g. position and momentum. A quasi-probability distribution resembles a probability distribution but may have negative and non-real entries. The most famous quasi-probability distribution, the Wigner function, has played a pivotal role in the development of a continuous-variable quantum theory that has clear analogues of position and momentum. However, the Wigner function is ill-suited for much modern quantum-information research, which is focused on finite-dimensional systems and general observables. Instead, recent years have seen the Kirkwood–Dirac (KD) distribution come to the forefront as a powerful quasi-probability distribution for analysing quantum mechanics. The KD distribution allows tools from statistics and probability theory to be applied to problems in quantum-information processing. A notable difference to the Wigner function is that the KD distribution can represent a quantum state in terms of arbitrary observables. This paper reviews the KD distribution, in three parts. First, we present definitions and basic properties of the KD distribution and its generalisations. Second, we summarise the KD distribution’s extensive usage in the study or development of measurement disturbance; quantum metrology; weak values; direct measurements of quantum states; quantum thermodynamics; quantum scrambling and out-of-time-ordered correlators; and the foundations of quantum mechanics, including Leggett–Garg inequalities, the consistent-histories interpretation and contextuality. We emphasise connections between operational quantum advantages and negative or non-real KD quasi-probabilities. Third, we delve into the KD distribution’s mathematical structure. We summarise the current knowledge regarding the geometry of KD-positive states (the states for which the KD distribution is a classical probability distribution), describe how to witness and quantify KD non-positivity, and outline relationships between KD non-positivity, coherence and observables’ incompatibility.

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Publication Details

Journal
New Journal of Physics
Published
2024-12-01
DOI
https://doi.org/10.1088/1367-2630/ada05d
Citations
37
Primary Topic
Quantum Mechanics and Applications
Type
article
Field-Weighted Citation Impact
12.49

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article

Properties and applications of the Kirkwood–Dirac distribution

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37 citations
New Journal of Physics
Quantum Mechanics and Applications
12.49
article

Properties and applications of the Kirkwood–Dirac distribution

Matteo Lostaglio, Justin Dressel, Nicole Yunger Halpern, William F. Braasch, Andrew N. Jordan, Jeff S. Lundeen, David R. M. Arvidsson-Shukur, Stephan De Bièvre, Christopher Langrenez
article en
37 citations

Abstract

Abstract There are several mathematical formulations of quantum mechanics. The Schrödinger picture expresses quantum states in terms of wavefunctions over, e.g. position or momentum. Alternatively, phase-space formulations represent states with quasi-probability distributions over, e.g. position and momentum. A quasi-probability distribution resembles a probability distribution but may have negative and non-real entries. The most famous quasi-probability distribution, the Wigner function, has played a pivotal role in the development of a continuous-variable quantum theory that has clear analogues of position and momentum. However, the Wigner function is ill-suited for much modern quantum-information research, which is focused on finite-dimensional systems and general observables. Instead, recent years have seen the Kirkwood–Dirac (KD) distribution come to the forefront as a powerful quasi-probability distribution for analysing quantum mechanics. The KD distribution allows tools from statistics and probability theory to be applied to problems in quantum-information processing. A notable difference to the Wigner function is that the KD distribution can represent a quantum state in terms of arbitrary observables. This paper reviews the KD distribution, in three parts. First, we present definitions and basic properties of the KD distribution and its generalisations. Second, we summarise the KD distribution’s extensive usage in the study or development of measurement disturbance; quantum metrology; weak values; direct measurements of quantum states; quantum thermodynamics; quantum scrambling and out-of-time-ordered correlators; and the foundations of quantum mechanics, including Leggett–Garg inequalities, the consistent-histories interpretation and contextuality. We emphasise connections between operational quantum advantages and negative or non-real KD quasi-probabilities. Third, we delve into the KD distribution’s mathematical structure. We summarise the current knowledge regarding the geometry of KD-positive states (the states for which the KD distribution is a classical probability distribution), describe how to witness and quantify KD non-positivity, and outline relationships between KD non-positivity, coherence and observables’ incompatibility.

New Journal of PhysicsVol. 26(12)
University of Ottawa (CA), Université de Lille (FR), University of Cambridge (GB), Park University (US), Hitachi (United Kingdom) (GB), Joint Center for Quantum Information and Computer Science (US), Laboratoire Paul Painlevé (FR), Laboratoire de Physique des Plasmas (FR), University of Rochester (US), University of Maryland, College Park (US), Wilfrid Laurier University (CA)
John Templeton Foundation, Agence Nationale de la Recherche, Canada Research Chairs, Centre National de la Recherche Scientifique, Girton College, University of Cambridge, Natural Sciences and Engineering Research Council of Canada, European Regional Development Fund
Openalex Percentile: Top 1%
Quantum Mechanics and Applications
12.49
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